Measuring the Early Impact of the ACA Through Public Opinion Polls and Surveys

1. Measuring the Early Impact of the ACA Through Public Opinion Polls and Surveys Challenges and Opportunities Mollyann Brodie, Ph.D Senior Vice President for Executive Operations and Executive Director, Public Opinion and Survey Research

3. What does everyone want to know? • How many previously uninsured got covered because of the ACA? • Thru Medicaid Expansions? • Thru Exchanges? • How many are still uninsured? • Why? Not eligible? Can’t afford? Don’t know about it? Too hard to sign up? • What are newly insured people’s experiences with signing up and getting health insurance? How is it changing/not changing their lives? • What do those who were PREVIOUSLY insured, but now have a new option (eg. new plan thru exchange/with a subsidy or new plan/no subsidy or now on Medicaid, before in non group market, etcetcetc ) think about their new coverage - is it better/ worse? More affordable/less? …AND THEY WANT IT NOW!

4. What do we know? • How many people enrolled in Medicaid • Hummmmm – were they previously eligible or newly eligible? • Hummmmm – were they previously uninsured or are they switching from non group? • How many people enrolled in health plans through exchanges • Hummmmm – were they previously uninsured? • Hummmmm – how much are they getting in subsidies? • How many people enrolled in private non group health plans • Hummmmm – were they previously uninsured?

5. Why is it so hard? • SMALL numbers • Lots of permutations • Starting points differ • Ending points differ • 50 states differ • Normal CHURN causes lots of noise – what’s ACA NEW and what’s just “normal” and what would’ve been the case WITHOUT the ACA • Churn in Medicaid • Churn in nongroup • Churn in employment coverage (get jobs/lose jobs) • Short spells of uninsurancevs long spells • Individuals DON’T understand – so self reporting messy and “noisy” • Public opinion surveys imperfect mechanisms

6. Challenges for National Public Opinion Polls • SMALL shares of relevant groups you care about on any probability based representative national survey • Online opt-in non probability panels provide large numbers, but not representative; particularly of populations we most want to know about (low income, Latino, Spanish speaking) • Many national polls conducted – but situations so different by states – fewer state surveys conducted • Questionnaire limitations – hard to figure out what box a given respondent belongs in, “burns” lots of time……. Most polls don’t have space to get questions accurate and comprehensive • Respondents are just confused…. Giving you the best information – still makes no sense

7. AN ILLUSTRATION: 190 Million Non-Elderly Adults Employer-Sponsored Insurance 58% Other 5 % Medicaid 11% Non-Group 5% Uninsured 21% SOURCE: DATA NOTE and State Health Facts

8. AN ILLUSTRATION: 190200 Million Non-Elderly Adults Survey Size: 2,000 1 box = 2 Million Adults = 20 Survey Adults Employer-Sponsored Insurance 58% Other 5 % Medicaid 11% Non-Group 5% Uninsured 21% SOURCE: DATA NOTE and State Health Facts

9. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults Employer-Sponsored Insurance Medicaid Other Non-Group Uninsured

10. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented Employer-Sponsored Insurance Medicaid Other Non-Group

11. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” Employer-Sponsored Insurance Medicaid Other Non-Group

12. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” • 22% are eligible for Medicaid Employer-Sponsored Insurance Medicaid Other Non-Group

13. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” • 22% are eligible for Medicaid Employer-Sponsored Insurance • Some of those eligible for Medicaid will enroll, some will remain uninsured Medicaid Other Non-Group

14. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” • 22% are eligible for Medicaid Employer-Sponsored Insurance • Some of those eligible for Medicaid will enroll, some will remain uninsured • 31% are eligible for subsidies in the exchanges Medicaid Other Non-Group

15. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” • 22% are eligible for Medicaid Employer-Sponsored Insurance • Some of those eligible for Medicaid will enroll, some will remain uninsured • 31% are eligible for subsidies in the exchanges • Some of those eligible for subsidies will enroll in the exchanges, some will remain uninsured Medicaid Other Non-Group

16. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” • 22% are eligible for Medicaid Employer-Sponsored Insurance • Some of those eligible for Medicaid will enroll, some will remain uninsured • 31% are eligible for subsidies in the exchanges • Some of those eligible for subsidies will enroll in the exchanges, some will remain uninsured Medicaid Other Non-Group • 21% are not eligible for financial assistance

17. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” • 22% are eligible for Medicaid Employer-Sponsored Insurance • Some of those eligible for Medicaid will enroll, some will remain uninsured • 31% are eligible for subsidies in the exchanges • Some of those eligible for subsidies will enroll in the exchanges, some will remain uninsured Medicaid Other Non-Group • 21% are not eligible for financial assistance • Some of those not eligible for financial assistance will purchase insurance, some will remain uninsured

18. 200 Million Non-Elderly AdultsSurvey Size: 2,0001 box = 2 Million Adults = 20 Survey Adults • 14% are undocumented • 12% live in states not Expanding Medicaid so fall into “Medicaid Gap” • 22% are eligible for Medicaid Employer-Sponsored Insurance • Some of those eligible for Medicaid will enroll, some will remain uninsured • 31% are eligible for subsidies in the exchanges • Some of those eligible for subsidies will enroll in the exchanges, some will remain uninsured Medicaid Other Non-Group • 21% are not eligible for financial assistance • Some of those not eligible for financial assistance will purchase insurance, some will remain uninsured

19. PROJECT 1: Panel Survey of Uninsured Californians Methodology • Four-wave Panel Survey: pre-open enrollment 2013, April 2014, late 2014 and 2015 (Wave 1 paid for by KFF; Wave 2-4 by The California Endowment) • Representative probability based random sample of 2,000 adults ages 18-64 living in California, who reported having been without health insurance coverage for at least two months • Telephone Interviews: 990 landline, 1011 cell phone (660 cell phone only) • Interviews conducted in English and Spanish • Demographics: • Race/Ethnicity 56% Hispanic, 26% White, 5% Black • Gender 54% Male, 46% Female • Age 57% 19-39, 21% 40-49, 22% 50-64 • Income 52% less than or equal to 138% FPL (Medi-Cal target), 36% between 139%-400% FPL (Exchange subsidy target), 7% over 400% FPL • 79% Eligible uninsured; 20% undocumented • 23% completed survey in Spanish for eligible uninsured- 37% for total uninsured

20. Opportunity and Challenges: Panel Survey of Uninsured Californians OPPORTUNITIES: • Focus on One starting point – One “Group” ; One State; One Initial Point in Time • The uninsured in California right before open enrollments starts • Track experiences of SAME people over time to see what happens to population • Longitudinal Panel vsPanel to select respondents from CHALLENGES: • Panel Attrition- uninsured are likely to be transient; potentially hard to re-contact for later waves of the survey • Panel Conditioning/Sensitization Effects- asking about health insurance status and the ACA may alter panelist opinions and behaviors • Only provides insight into one policy environment, for one population • Expensive

21. What Comes Next With CA Uninsured? • Second Wave of the Survey April 2014, release May-June 2014 • We will track the same group of Californians: • What choices did they make? • Who enrolled in Medi-Cal and why, or why not? • Who shopped on the state’s new exchange, and how do they evaluate that experience and the coverage they got there? • Has expanded access to health insurance made a dent in the level of worry people without coverage currently experience in viewing an uncertain future? • What do those who remained uninsured plan to do in the future? Why are they still uninsured? • We will follow up over the longer term with a third and fourth wave of interviews to fully capture the views and experiences of the state’s uninsured throughout the first two years of the ACA insurance expansion

22. PROJECT 2: KFF National and State Specific Low Income Survey - Methodology • Baseline Survey: National, plus 3 state-specific samples (CA, MO, TX) • Fielded Summer 2013 (July 24 – Sept 29) • Total Interviews: 8,762 (including 2,558 in CA, 1,872 in MO, 1,809 in TX and 2,523 in other states) • Includes all income groups, with focus on those with lower incomes targeted for coverage expansion using large oversamples • Allows for findings by income group (=<138% FPL, 139%-400% FPL, 400%+ FPL), and insurance status (uninsured, ESI, nongroup, etc). • English and Spanish, cell/LL • Partners – Blue Shield Foundation of CA and Missouri Foundation for Health

23. Sample Sizes of Key Groups

24. Opportunity and Challenges – Cross Sectional Surveys Over time – KFF Low Income Survey Project OPPORTUNITIES: • Large sample size nationally and in 3 key states • Ability to break out relevant income groups • No need to keep track of panelists • Wave 1 provides a baseline, can follow up to measure change among key groups in wave 2 • Track experiences of key population groups over time nationally, and in some key states to shed light on what happens to particular population groups nationally and in a few sentinel states CHALLENGES: • Patience required……. Will be a year or so before we can “shed” light (and many changes will take even longer to be measurable) • Tracking groups, not individuals…. In wave 2 will need to try to capture where an individual “was” in terms of their health care situation a year earlier • Expensive • Sample Size STILL a challenge for looking at some targeted groups (eg AAPI)

25. What Comes Next With KFF Low Income Survey? • Later wave(s): Substantially increase the number of low and moderate income interviews so we can talk about those who remained uninsured, and those who are newly covered by Medicaid or the exchange plans. • Wave 2 - likely early 2015

26. PROJECT 3: Ongoing Monthly Health Tracking Poll • Nationally representative random digit dial telephone sample of 1,200-1,500 adults ages 18 and older, living in the United States, including Alaska and Hawaii • Interviews conducted by landline and cellphone • Interviews conducted in English and Spanish • The Foundation began conducting regular bi-monthly surveys of the public on health policy topics in 1996, and increased the frequency of these surveys to monthly in 2009. • Since 2009, we have conducted a total of ~72,000 interviews

27. Opportunity and Challenges: Monthly Health Tracking Polls OPPORTUNITIES: • Regular, quick, timely • Can track changes in national opinion, knowledge, confusion and broad experiences • Long time trend allows for historical perspective • Cheaper CHALLENGES: • Can’t talk about many of the small subgroups people most want to know about • Variation over time in small groups can just be statistical noise